Procedural outline

Turn on machines / heaters. Put mice in tailcuff room and let the room and mice acclimate to appropriate temperature for ~30-60 mins. Then, check cuffs for leaks. Put mice into restraints and perform 5 acclimation cycles + 20 recorded cycles.

When placing mice into restraints,
1. Quickly place nose cuff on to avoid letting them turn around in the restraint
2. Make sure that you can see them breathing…
3. Maximize tightness of fit and breathing

Metadata Analysis

This workbook is set up to analyze two groups of mice! Just run and enjoy (you’ll probably need to change out drug names…)

Metadata
group Specimen Name Mouse Unique ID Gender Notch DOB Wean Date CageID Current Age (weeks) Date ready for Telemetry implant New CageID Status Date of death Machine ID Average body weight (g)
vehicle M1 1A Male NN 2021-03-25 2021-04-20 662055 11.71429 2021-05-20 NA Alive NA 1 26.100
sorafenib M2 2A Male RN 2021-03-25 2021-04-20 662055 11.71429 2021-05-20 NA Alive NA 1 24.200
sorafenib M3 3A Male LN 2021-03-25 2021-04-20 662055 11.71429 2021-05-20 NA Alive NA 1 24.750
vehicle M4 4A Male BN 2021-03-25 2021-04-20 662055 11.71429 2021-05-20 NA Alive NA 1 25.275
sorafenib M5 5A Male DR 2021-03-25 2021-04-20 662055 11.71429 2021-05-20 NA Alive NA 1 26.375
sorafenib M6 1B Male NN 2021-03-30 2021-04-13 662047 11.00000 2021-05-25 NA Alive NA 2 23.725
vehicle M7 2B Male RN 2021-03-30 2021-04-13 662047 11.00000 2021-05-25 NA Alive NA 2 24.675
sorafenib M8 3B Male LN 2021-03-30 2021-04-13 662047 11.00000 2021-05-25 NA Alive NA 2 23.800
sorafenib M9 4B Male BN 2021-03-30 2021-04-13 662047 11.00000 2021-05-25 NA Alive NA 2 22.800
vehicle M10 5B Male DR 2021-03-30 2021-04-13 662047 11.00000 2021-05-25 NA Alive NA 2 24.150

Inspect accepted cycles and changes in mouse body weight over time

Average animal body weight

Animal body weight change over time

Blood Pressure Data Analysis

Filtering out days that had less than ‘x’ cycles

Removed days/Specimens with less than 5 cycles:
Specimen Name Date group # cycles reason
M3 2021-05-25 sorafenib 1 Low cycle count
M7 2021-05-25 vehicle 4 Low cycle count

Removing outliers

Detect outliers BP measurements using boxplot methods. Boxplots are a popular and an easy method for identifying outliers. There are two categories of outlier: (1) outliers and (2) extreme points. Values above Q3 + 2xIQR or below Q1 - 2xIQR are considered as outliers. Q1 and Q3 are the first and third quartile, respectively. IQR is the interquartile range (IQR = Q3 - Q1). This method is more robust than STDEV based outlier detection because outliers can skew the mean and STDEV of a sample.

Here, outliers are nominated based on daily blood pressure recordings, so as to not throw out data on treatment days when the blood pressure is expected to rise above the average.

Additionally, we remove mice that are too ‘volatile’ after trianing period has finished.

Plot the data over time and visualize the variance per day, per sample with boxplots, over all days

Pilot 2 | sorafenib 100 mg/kg/d

Dates
Phase first last date_range Number of Days
training 2021-05-25 2021-05-28 2021-05-25 to 2021-05-28 4
vehicle 2021-05-29 2021-06-02 2021-05-29 to 2021-06-02 5
treatment 2021-06-03 2021-06-09 2021-06-03 to 2021-06-09 7

Assess BP of randomly assigned groups before getting treatment

3-day rolling average

Take the last 3-days of an interval and average them for more realistic averages

Assess heart rate changes per mouse and between groups

Time-series data

For completeness, here is the time series data of each mouse across each Phase of the experiment:

Time-series diff by individual mouse from vehicle average to end of treatment

Time-series diff by group

These are the average blood pressures of each mice across each Phase of the experiment

Booklet usage instructions

Download excel data after finishing the experiments onto thumb drive

Copy the data into a master excel file with two sheets, making sure that there’s only one header (at the very top of the page).

  1. You’ll need to add in two columns manually to this master sheet: Date and Phase. Phase can take one of 4 values: “training”, “baseline”, “vehicle”, “treatment”. Training data ultimately gets removed, but included in the data sheet for completeness. First sheet should look like this:
    Metadata
    Specimen Name Systolic Mean Rate Cycle # Date Phase
    M1 120 99 666 11 2021-05-25 training
    M1 116 102 684 12 2021-05-25 training
    M1 111 90 643 13 2021-05-25 training
    M1 101 85 678 14 2021-05-25 training
    M1 109 93 644 15 2021-05-25 training
    M1 106 88 664 16 2021-05-25 training
  2. Second sheet should be created manually based on your mice. Fill in the various fields.
    Metadata
    Specimen Name Mouse Unique ID Gender Notch DOB Wean Date CageID Current Age (weeks) Date ready for Telemetry implant New CageID Body weight (g) Date Status Date of death Machine ID
    M1 1A Male NN 2021-03-25 2021-04-20 662055 11.71429 2021-05-20 NA 26.4 2021-05-25 Alive NA 1
    M2 2A Male RN 2021-03-25 2021-04-20 662055 11.71429 2021-05-20 NA 24.9 2021-05-25 Alive NA 1
    M3 3A Male LN 2021-03-25 2021-04-20 662055 11.71429 2021-05-20 NA 26.2 2021-05-25 Alive NA 1
    M4 4A Male BN 2021-03-25 2021-04-20 662055 11.71429 2021-05-20 NA 25.7 2021-05-25 Alive NA 1
    M5 5A Male DR 2021-03-25 2021-04-20 662055 11.71429 2021-05-20 NA 27.5 2021-05-25 Alive NA 1
    M6 1B Male NN 2021-03-30 2021-04-13 662047 11.00000 2021-05-25 NA 25.1 2021-05-25 Alive NA 2
    M7 2B Male RN 2021-03-30 2021-04-13 662047 11.00000 2021-05-25 NA 25.7 2021-05-25 Alive NA 2
    M8 3B Male LN 2021-03-30 2021-04-13 662047 11.00000 2021-05-25 NA 24.9 2021-05-25 Alive NA 2
    M9 4B Male BN 2021-03-30 2021-04-13 662047 11.00000 2021-05-25 NA 23.4 2021-05-25 Alive NA 2
    M10 5B Male DR 2021-03-30 2021-04-13 662047 11.00000 2021-05-25 NA 25.3 2021-05-25 Alive NA 2